Data-driven single-objective optimization using a reference vector guided multi-objective infill criterion and Louvain-based local search

doi:10.1016/j.asoc.2026.116124

Data-driven single-objective optimization using a reference vector guided multi-objective infill criterion and Louvain-based local search

2026-07-30

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DOI：10.1016/j.asoc.2026.116124

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Data-driven single-objective optimization via multi-objective infill strategy. Proposed bi-objective infill criterion adaptively balances exploitation-exploration. Louvain-based subspace identification enables focused search in promising regions. Validated on 10-100D test benchmarks and underwater glider shape optimization.

Data-driven single-objective optimization using a reference vector guided multi-objective infill criterion and Louvain-based local search

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